# ---- Datasets
dat1 <- readRDS('data/Panama2012.RDS') %>% mutate(PlaceName = 'Darien', id = stringr::str_sub(dataset_id, 1, 3))
dat2 <- readRDS('data/Panama2017.RDS') %>% mutate(PlaceName = 'Mogue', id = stringr::str_sub(dataset_id, 1, 3))
dat3 <- readRDS('data/Panama2012_places.RDS')%>% mutate(survey = dataset_id)
dat0 <- rbind(dat3, dat1, dat2) %>% filter(id %in% c('005', '010'))
dat0$virus[dat0$virus=='UNA'] <- 'UNAV'
dat0 <- dat0 %>% mutate(counts = pos,
survey = paste(virus,tsur, PlaceName, id)) %>%
arrange(desc(survey)) %>% mutate(age_mean_f = floor((age_min + age_max)/2))
(datasets <- unique(dat0$survey))
for (s in datasets)
{
dat <- filter(dat0, survey == s) %>% arrange(age_mean_f) %>%
mutate(birth_year = tsur - age_mean_f)
res <- fFitModel(model_d, dat)
loo_res <- loo::loo(res$fit, save_psis = TRUE, 'logLikelihood')
plot_res <- fPlotModel(res, dat, 'model dec', 'Student_t')
res_survey <- list(dat = dat,
res = res,
loo_res = loo_res,
plot_res = plot_res)
saveRDS(res_survey, paste0('res/mod_decs', s, '.RDS' ))
print(plot_res)
rm(dat, res, loo_res, plot_res, res_survey)
}





























